gpt-oss-120b
gpt-oss-120b
Version: 4
OpenAILast updated December 2025
Push the open model frontier with GPT-OSS models, released under the permissive Apache 2.0 license, allowing anyone to use, modify, and deploy them freely.
Reasoning
Multilingual
Coding

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Key capabilities

About this model

The provider has not supplied this information.

Key model capabilities

  • Permissive Apache 2.0 license: Build freely without copyleft restrictions or patent risk—ideal for experimentation, customization, and commercial deployment.
  • Configurable reasoning effort: Easily adjust the reasoning effort (low, medium, high) based on your specific use case and latency needs.
  • Full chain-of-thought: Gain complete access to the model's reasoning process, facilitating easier debugging and increased trust in outputs. It's not intended to be shown to end users.
  • Fine-tunable: Fully customize models to your specific use case through parameter fine-tuning.
  • Agentic capabilities: Use the models' native capabilities for function calling, web browsing , Python code execution , and Structured Outputs.
  • Native MXFP4 quantization: The models are trained with native MXFP4 precision for the MoE layer, making gpt-oss-120b run on a single H100 GPU and the gpt-oss-20b model run within 16GB of memory.

Use cases

See Responsible AI for additional considerations for responsible use.

Key use cases

The provider has not supplied this information.

Out of scope use cases

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Pricing

Pricing is based on a number of factors, including deployment type and tokens used. See pricing details here.

Technical specs

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Training cut-off date

The provider has not supplied this information.

Training time

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Input formats

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Output formats

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Supported languages

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Sample JSON response

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Model architecture

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Long context

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Optimizing model performance

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Additional assets

Please see OpenAI's gpt-oss-120b model card here.

Training disclosure

Training, testing and validation

The provider has not supplied this information.

Distribution

Distribution channels

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More information

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Responsible AI considerations

Safety techniques

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Safety evaluations

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Known limitations

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Acceptable use

Acceptable use policy

The provider has not supplied this information.

Quality and performance evaluations

Source: OpenAI The provider has not supplied this information.

Benchmarking methodology

Source: OpenAI The provider has not supplied this information.

Public data summary

Source: OpenAI The provider has not supplied this information.
Model Specifications
Context Length131072
Quality Index0.85
LicenseCustom
Last UpdatedDecember 2025
Input TypeText
Output TypeText
ProviderOpenAI
Languages1 Language